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Education savings accounts (ESAs) are education funding mechanisms that allow for families to receive a deposit of public funds to a government-authorized savings account. Using student-level longitudinal data, this paper examines how families participating in the Florida Gardiner Scholarship Program use education savings account funds. Results indicate that families use an increasing proportion of ESA funds the longer students remain in the program. The longer students remain in the program, the share of ESA funds devoted to private school tuition decreases while expenditure shares increase for curriculum, instruction, tutoring, and specialized services. Students in rural areas not only use a greater portion of their ESA funds than families in urban and suburban areas, but they also spend smaller portions of their funds on tuition and appear to customize more.
In conversation, uptake happens when a speaker builds on the contribution of their interlocutor by, for example, acknowledging, repeating or reformulating what they have said. In education, teachers' uptake of student contributions has been linked to higher student achievement. Yet measuring and improving teachers' uptake at scale is challenging, as existing methods require expensive annotation by experts. We propose a framework for computationally measuring uptake, by (1) releasing a dataset of student-teacher exchanges extracted from US math classroom transcripts annotated for uptake by experts; (2) formalizing uptake as pointwise Jensen-Shannon Divergence (pJSD), estimated via next utterance classification; (3) conducting a linguistically-motivated comparison of different unsupervised measures and (4) correlating these measures with educational outcomes. We find that although repetition captures a significant part of uptake, pJSD outperforms repetition-based baselines, as it is capable of identifying a wider range of uptake phenomena like question answering and reformulation. We apply our uptake measure to three different educational datasets with outcome indicators. Unlike baseline measures, pJSD correlates significantly with instruction quality in all three, providing evidence for its generalizability and for its potential to serve as an automated professional development tool for teachers.
Advanced course-taking in high school sends an important signal to college admissions officers, helps reduce the cost and time to complete a post-secondary degree, and increases educational attainment and future earnings. However, Black and Hispanic students in the U.S. are underrepresented in Advanced Placement coursework and dual enrollment (i.e. early college). In this paper, we systematically examine the social, demographic, economic, and policy factors that are predictive of racial gaps in AP enrollment and access to DE across the U.S. We find that many of the same factors that predict higher AP access overall also predict higher racial/ethnic gaps in AP, suggesting that policies aimed at increasing AP access need to specifically attend to the inequitable access, rather than simply focusing on increasing access overall. We also find evidence that that might indicate opportunity hoarding by White families contributes to AP gaps – but not DE gaps – suggesting that DE acts as a more equitable avenue for access to college coursework. Our most novel contribution to the literature is our analysis of policies aimed at reducing teacher shortages in high needs areas, in which we find no evidence that the disparities in access to advanced coursework were reduced following implementation of these policies.
In multisite experiments, we can quantify treatment effect variation with the cross-site treatment effect variance. However, there is no standard method for estimating cross-site treatment effect variance in multisite regression discontinuity designs (RDD). This research rectifies this gap in the literature by systematically exploring and evaluating methods for estimating the cross-site treatment effect variance in multisite RDDs. Specifically, we formalize a fixed intercepts/random coefficients (FIRC) RDD model and develop a random effects meta-analysis (Meta) RDD model for estimating cross-site treatment effect variance. We find that a restricted FIRC model works best when the running variables' relationship to the outcome is stable across sites but can be biased otherwise. In those instances, we recommend using either the unrestricted FIRC model or the meta-analysis model; with the unrestricted FIRC model generally performing better when the average number of in-bandwidth observations is less than 120 and the meta-analysis model performing better when the average number of in-bandwidth observations is above 120. We apply our models to a high school exit exam policy in Massachusetts that required students who passed the high school exit exam but were still determined to be nonproficient to complete an ``Education Proficiency Plan" (EPP). We find the EPP policy had a positive local average treatment effect on whether students completed a math course their senior year on average across sites, but that the impact varied enough such that a third of schools could have had a negative impact.
Federal law defines eligibility for English learner (EL) classification differently for Indigenous students compared to non-Indigenous students. Indigenous students, unlike non-Indigenous students, are not required to have a non-English home or primary language. A critical question, therefore, is how EL classification impacts Indigenous students’ educational outcomes. This study explores this question for Alaska Native students, drawing on data from five Alaska school districts. Using a regression discontinuity design, we find evidence that among students who score near the EL classification threshold in kindergarten, EL classification has a large negative impact on Alaska Native students’ academic outcomes, especially in the 3rd and 4th grades. Negative impacts are not found for non-Alaska Native students in the same districts.
Cultural capital is influential in determining who continues on to and succeeds in higher education. However, scholars debate whether cultural capital serves to reproduce existing inequalities or provide a path to upward mobility. Most quantitative studies focus on point-in-time correlations between cultural capital measures and educational achievement or attainment. Thus, this work is unclear on how or even if disadvantaged adolescents can significantly increase their stores of cultural capital. One potential way of providing adolescents with an opportunity to gain cultural capital is through ties to adults with high educational attainment. We investigate this topic using unique quasi-experimental longitudinal data on mentoring relationships between adolescents and adults in the Big Brothers/Big Sisters of America program. We find that only mentors with a college degree or greater have positive effects on cultural capital for adolescents. Furthermore, most of the effects of social capital on cultural capital hold only for adolescents with a parent with some college or greater. We question whether cultural capital can truly be an engine of social mobility if adolescents from low-SES households cannot obtain or increase their cultural capital.
A core motivation for the widespread teacher evaluation reforms of the last decade was the belief that these new systems would promote teacher development through high-quality feedback. We examine this theory by studying teachers’ perceptions of evaluation feedback in Boston Public Schools and evaluating the district’s efforts to improve feedback through an administrator training program. Teachers generally reported that evaluators were trustworthy, fair, and accurate, but that they struggled to provide high-quality feedback. We find little evidence the training program improved perceived feedback quality, classroom instruction, teacher self-efficacy, or student achievement. Our results illustrate the challenges of using evaluation systems as engines for professional growth when administrators lack the time and skill necessary to provide frequent, high-quality feedback.
From 2010 onwards, most US states have aligned their education standards by adopting the Common Core State Standards (CCSS) for math and English Language Arts. The CCSS did not target other subjects such as science and social studies. We estimate spillovers of the CCSS on student achievement in non-targeted subjects in models with state and year fixed effects. Using student achievement data from the NAEP, we show that the CCSS had a negative effect on student achievement in non-targeted subjects. This negative effect is largest for underprivileged students, exacerbating racial and socioeconomic student achievement gaps. Using teacher surveys, we show that the CCSS caused a reduction in instructional focus on nontargeted subjects.
The ongoing crisis in teacher pension funding has led states to consider various reforms in plan design, to replace the traditional benefit formulas, based on years of service and final average salary (FAS). One such design is a cash balance (CB) plan, long deployed in the private sector, and increasingly considered, but rarely yet adopted for teachers. Such plans are structured with individual 401(k)-type retirement accounts, but with guaranteed returns. In this paper I examine how the nation’s first CB plan for teachers, in Kansas, has played out for system costs, and the level and distribution of individual benefits, compared to the FAS plan it replaced. My key findings are: (1) employer-funded benefits were modestly reduced, despite the surface appearance of more generous employer contribution matches; (2) more importantly, the cost of the pension guarantee, which is off-the-books under standard actuarial accounting, was reduced quite substantially. In addition, benefits are more equitably distributed between short termers and career teachers than under the back-loaded structure of benefits characteristic of FAS plans. The key to the plan’s cost reduction is that the guaranteed return approximates a low-risk market return, considerably lower than the assumed return on risky assets.
Four-day school weeks have proliferated across the United States in recent years, reaching over 650 public school districts in 24 states as of 2019, but little is known about the effects of the four-day school week on high school students. This study uses district-level panel data from Oklahoma and a difference-in-differences research design to provide the first estimates of the causal effect of the four-day school week on high school students’ ACT scores, attendance, and disciplinary incidents during school. Results indicate that four-day school weeks decrease per-pupil bullying incidents by approximately 31% and per-pupil fighting incidents by approximately 27%, but have no detectable effect on other incident types, ACT scores, or attendance.